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Call for papers - AI in patient monitoring and diagnostics

Guest Editor

Sahil Thakur, MBBS, MS, Singapore Eye Research Institute, Singapore

Submission Status: Open   |   Submission Deadline: 18 December 2024

BMC Ophthalmology is calling for submissions to our Collection on the use of artificial intelligence in Ophthalmology.

Meet the Guest Editor

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Sahil Thakur, MBBS, MS, Singapore Eye Research Institute, Singapore

Dr Sahil Thakur completed his ophthalmology training (MS, MBBS) from Government Medical College and Hospital, Chandigarh, India. He is currently a Clinical Research Fellow at the Singapore Eye Research Institute. Apart from pursuing clinical ophthalmology, he has a keen interest in developing affordable diagnostic tools for addressing unmet public healthcare requirements. He has co-authored a book, Smart Resources in Ophthalmology: Applications and Social Networking and has co-edited a book, Artificial Intelligence and Ophthalmology: Perks, Perils and Pitfalls. In addition to these he has published more than 80 peer-reviewed articles and is on the editorial board of BMC Ophthalmology.


About the Collection

BMC Ophthalmology is calling for submissions to our Collection on the use of artificial intelligence in Ophthalmology.

The integration of Artificial Intelligence (AI) into ophthalmic diagnostics and patient monitoring is crucial for improving diagnostic accuracy, optimizing patient care, and resource allocation, ultimately leading to better treatment outcomes in eye care. AI technologies have the potential to streamline processes, enhance accessibility, and drive innovation in ophthalmology, benefiting both patients and healthcare systems worldwide. This Collection brings together contributions that explore its diverse applications across various domains of ophthalmology. Topics accepted for publication include:

AI-driven algorithms for the early detection and classification of ocular diseases. Development and validation of AI-based imaging techniques for retinal analysis. Application of machine learning and deep learning methodologies for analyzing ophthalmic datasets. Real-world implementation studies and clinical trials evaluating the efficacy of AI-enabled solutions in ophthalmology practice. Innovations in teleophthalmology and remote monitoring facilitated by AI-driven telemedicine platforms.

Image credit: Олександр Луценко /

There are currently no articles in this collection.

Submission Guidelines

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This Collection welcomes submission of original Research Articles. Should you wish to submit a different article type, please read our submission guidelines to confirm that type is accepted by the journal. Articles for this Collection should be submitted via our submission system, Snapp. During the submission process you will be asked whether you are submitting to a Collection, please select "AI in patient monitoring and diagnostics" from the dropdown menu.

Articles will undergo the journal’s standard peer-review process and are subject to all of the journal’s standard policies. Articles will be added to the Collection as they are published.

The Editors have no competing interests with the submissions which they handle through the peer review process. The peer review of any submissions for which the Editors have competing interests is handled by another Editorial Board Member who has no competing interests.